Big Data

Today, unprecedented amounts of data are being generated at a very rapid rate. This is thanks to the rise of the internet and social media; the ubiquity of smart phones and miniature sensing devices; the increasing effectiveness of scientific instruments at collecting data like genomic data, astronomical data, medical data, etc.; and increasing use of computational tools, especially simulations, in social and physical sciences. Traditional data processing applications like relational database systems are often unable to handle such "big data" for several reasons. The scale of the data is often much higher than traditional data management tools are equipped to handle. The data tends to come from a variety of disparate sources and exhibits high heterogeneity and variety. The data is often generated at very high rate (velocity). Finally, the data is often noisy and the veracity of the data can be hard to evaluate. Managing and analyzing "big data" requires fundamentally new techniques and systems. Aside from the challenges mentioned above, because of the increasing ability to capture and correlate personal data, security and privacy issues become paramount. The Computer Science Department at the University of Maryland is pursuing a comprehensive research agenda that addresses all aspects of big data management, spanning the fields of high performance computing, databases, cloud computing, distributed systems, visualization, and security and privacy.

Associated Faculty

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Recent News

PhD student Noseong Park, postdoctoral fellow Edoardo Serra, and Professor and Director of the Lab for Computational Cultural Dynamics and Center for Digital International Government V.S...
The department is pleased to announce the appointment of three new affiliate faculty members: Niklas Elmqvist, Vanessa Frias-Martinez, and Richard Marciano.